CHAPTER 2:
MODELING DATA IN THE ORGANIZATION
Essentials of Database Management
Jeffrey A. Hoffer, Heikki Topi, V. Ramesh
Copyright © 2014 Pearson Education, Inc.
1
OBJECTIVES








Define terms
Understand importance of data modeling
Write good names and definitions for entities, relationships,
and attributes
Distinguish unary, binary, and ternary relationships
Model different types of attributes, entities, relationships,
and cardinalities
Draw E-R diagrams for common business situations
Convert many-to-many relationships to associative entities
Model time-dependent data using time stamps
Chapter 2
Copyright © 2014 Pearson Education, Inc.
2
E-R MODEL CONSTRUCTS

Entities:



Relationships:



Entity instance–person, place, object, event, concept (often
corresponds to a row in a table)
Entity Type–collection of entities (often corresponds to a table)
Relationship instance–link between entities (corresponds to
primary key–foreign key equivalencies in related tables)
Relationship type–category of relationship…link between entity
types
Attributes:

Properties or characteristics of an entity or relationship type (often
corresponds to a field in a table)
Chapter 2
Copyright © 2014 Pearson Education, Inc.
3
Sample E-R Diagram (Figure 2-1)
Chapter 2
Copyright © 2014 Pearson Education, Inc.
4
Basic E-R notation (Figure 2-2)
Entity
symbols
Attribute
symbols
A special entity
that is also a
relationship
Relationship
symbols
Relationship
degrees specify
number of
entity types
involved
Chapter 2
Relationship
cardinalities
specify how
many of each
entity type is
allowed
Copyright © 2014 Pearson Education, Inc.
5
BUSINESS RULES






Are statements that define or constrain some
aspect of the business
Are derived from policies, procedures, events,
functions
Assert business structure
Control/influence business behavior
Are expressed in terms familiar to end users
Are automated through DBMS software
Chapter 2
Copyright © 2014 Pearson Education, Inc.
6
A GOOD BUSINESS RULE IS:
 Declarative–what,
not how
 Precise–clear, agreed-upon meaning
 Atomic–one statement
 Consistent–internally and externally
 Expressible–structured, natural language
 Distinct–non-redundant
 Business-oriented–understood by
business people
Chapter 2
Copyright © 2014 Pearson Education, Inc.
7
DATA DEFINITIONS

Explanation of a term or fact
 Term–word
or phrase with specific meaning
 Fact–association between two or more terms

Guidelines for good data definition
A
concise description of essential data meaning
 Gathered in conjunction with systems
requirements
 Accompanied by diagrams
 Achieved by consensus, and iteratively refined
Chapter 2
Copyright © 2014 Pearson Education, Inc.
8
A GOOD DATA NAME IS:







Related to business, not technical, characteristics
Meaningful and self-documenting
Unique
Readable
Composed of words from an approved list
Repeatable
Written in standard syntax
Chapter 2
Copyright © 2014 Pearson Education, Inc.
9
ENTITIES
 Entity
– a person, a place, an object, an
event, or a concept in the user
environment about which the organization
wishes to maintain data
 Entity type – a collection of entities that
share common properties or
characteristics
 Entity instance – A single occurrence of
an entity type
Chapter 2
Copyright © 2014 Pearson Education, Inc.
10
ENTITY TYPE AND ENTITY INSTANCES
Chapter 2
Copyright © 2014 Pearson Education, Inc.
11
AN ENTITY…

SHOULD BE:
 An
object that will have many instances in the
database
 An object that will be composed of multiple
attributes
 An object that we are trying to model

SHOULD NOT BE:
A
user of the database system
 An output of the database system (e.g., a
report)
Chapter 2
Copyright © 2014 Pearson Education, Inc.
12
Figure 2-4 Example of inappropriate entities
System
user
Inappropriate
entities
System
output
Appropriate
entities
Chapter 2
Copyright © 2014 Pearson Education, Inc.
13
STRONG VS. WEAK ENTITIES, AND
IDENTIFYING RELATIONSHIPS

Strong entity


exists independently of other types of entities
has its own unique identifier


Weak entity




identifier underlined with single line
dependent on a strong entity (identifying owner)…cannot
exist on its own
does not have a unique identifier (only a partial identifier)
entity box and partial identifier have double lines
Identifying relationship

links strong entities to weak entities
Chapter 2
Copyright © 2014 Pearson Education, Inc.
14
Figure 2-5 Example of a weak identity and its identifying relationship
Strong entity
Chapter 2
Weak entity
Copyright © 2014 Pearson Education, Inc.
15
ATTRIBUTES
 Attribute–property
or characteristic of
an entity or relationship type
 Classifications of attributes:
 Required
versus Optional Attributes
 Simple versus Composite Attribute
 Single-Valued versus Multivalued Attribute
 Stored versus Derived Attributes
 Identifier Attributes
Chapter 2
Copyright © 2014 Pearson Education, Inc.
16
REQUIRED VS. OPTIONAL ATTRIBUTES
Required – must have a value for every
entity (or relationship) instance with
which it is associated
Chapter 2
Optional – may not have a value for
every entity (or relationship) instance
with which it is associated
Copyright © 2014 Pearson Education, Inc.
17
SIMPLE VS. COMPOSITE ATTRIBUTES

Composite attribute – An attribute that has
meaningful component parts (attributes)
The address is
broken into
component parts
Figure 2-7 A composite attribute
Chapter 2
Copyright © 2014 Pearson Education, Inc.
18
Multi-valued and Derived
Attributes
Multivalued – may take on more than
one value for a given entity (or
relationship) instance
Derived – values can be calculated from
related attribute values (not physically
stored in the database)
Figure 2-8 Entity with multivalued attribute (Skill) and derived attribute
(Years Employed)
Multivalued
an employee can
have more than one
skill
Chapter 2
Copyright © 2014 Pearson Education, Inc.
Derived
Calculated
from date
employed
and current
date
19
IDENTIFIERS (KEYS)
 Identifier
(Key)–an attribute (or
combination of attributes) that uniquely
identifies individual instances of an entity
type
 Simple versus Composite Identifier
 Candidate Identifier–an attribute that
could be a key…satisfies the requirements
for being an identifier
Chapter 2
Copyright © 2014 Pearson Education, Inc.
20
CRITERIA FOR IDENTIFIERS
 Choose
Identifiers that
 Will
not change in value
 Will not be null
 Avoid
intelligent identifiers (e.g.,
containing locations or people that
might change)
 Substitute new, simple keys for long,
composite keys
Chapter 2
Copyright © 2014 Pearson Education, Inc.
21
Figure 2-9 Simple and composite identifier attributes
The identifier
is boldfaced
and underlined
Chapter 2
Copyright © 2014 Pearson Education, Inc.
22
NAMING ATTRIBUTES
 Name
should be a singular noun or noun
phrase
 Name should be unique
 Name should follow a standard format
 e.g.
[Entity type name { [ Qualifier ] } ] Class
 Similar
attributes of different entity types
should use the same qualifiers and
classes
Chapter 2
Copyright © 2014 Pearson Education, Inc.
23
DEFINING ATTRIBUTES







State what the attribute is and possibly why it is
important
Make it clear what is and is not included in the
attribute’s value
Include aliases in documentation
State source of values
Specify required vs. optional
State min and max number of occurrences allowed
Indicate relationships with other attributes
Chapter 2
Copyright © 2014 Pearson Education, Inc.
24
MODELING RELATIONSHIPS

Relationship Types vs. Relationship Instances


Relationships can have attributes



The relationship type is modeled as lines between
entity types…the instance is between specific entity
instances
These describe features pertaining to the association between
the entities in the relationship
Two entities can have more than one type of
relationship between them (multiple
relationships)
Associative Entity–combination of relationship
and entity
Chapter 2
Copyright © 2014 Pearson Education, Inc.
25
Figure 2-10 Relationship types and instances
a) Relationship
type (Completes)
b) Relationship
instances
Chapter 2
Copyright © 2014 Pearson Education, Inc.
26
DEGREE OF RELATIONSHIPS
Degree
of a relationship is the
number of entity types that
participate in it
Unary
Relationship
Binary Relationship
Ternary Relationship
Chapter 2
Copyright © 2014 Pearson Education, Inc.
27
Degree of relationships – from Figure 2-2
One entity
related to
another of
the same
entity type
Chapter 2
Entities of
two different
types related
to each other
Entities of three
different types
related to each
other
Copyright © 2014 Pearson Education, Inc.
28
CARDINALITY OF RELATIONSHIPS

One-to-One
 Each
entity in the relationship will have exactly one
related entity

One-to-Many
 An
entity on one side of the relationship can have
many related entities, but an entity on the other
side will have a maximum of one related entity

Many-to-Many
 Entities
on both sides of the relationship can have
many related entities on the other side
Chapter 2
Copyright © 2014 Pearson Education, Inc.
29
Figure 2-12 Examples of relationships of different degrees
a) Unary relationships
Chapter 2
Copyright © 2014 Pearson Education, Inc.
30
Figure 2-12 Examples of relationships of different degrees (cont.)
b) Binary relationships
Chapter 2
Copyright © 2014 Pearson Education, Inc.
31
Figure 2-12 Examples of relationships of different degrees (cont.)
c) Ternary relationship
Note: a relationship can have attributes of its own
Chapter 2
Copyright © 2014 Pearson Education, Inc.
32
CARDINALITY CONSTRAINTS
 Cardinality
Constraints—the number of
instances of one entity that can or must
be associated with each instance of
another entity
 Minimum Cardinality
 If
zero, then optional
 If one or more, then mandatory
 Maximum
 The
Chapter 2
Cardinality
maximum number
Copyright © 2014 Pearson Education, Inc.
33
Figure 2-17 Examples of cardinality constraints
a) Mandatory cardinalities
A patient history is
recorded for one and
only one patient
Chapter 2
A patient must have recorded
at least one history, and can
have many
Copyright © 2014 Pearson Education, Inc.
34
Figure 2-17 Examples of cardinality constraints (cont.)
b) One optional, one mandatory
A project must be
assigned to at least one
employee, and may be
assigned to many
Chapter 2
An employee can be assigned
to any number of projects, or
may not be assigned to any
at all
Copyright © 2014 Pearson Education, Inc.
35
Figure 2-17 Examples of cardinality constraints (cont.)
c) Optional cardinalities
A person is
married to at most
one other person,
or may not be
married at all
Chapter 2
Copyright © 2014 Pearson Education, Inc.
36
Figure 2-20 Examples of multiple relationships
a) Employees and departments
Entities can be related to one another in more than one way
Chapter 2
Copyright © 2014 Pearson Education, Inc.
37
Figure 2-20 Examples of multiple relationships (cont.)
b) Professors and courses (fixed lower limit constraint)
Here, min cardinality constraint is 2. At least two
professors must be qualified to teach each course. Each
professor must be qualified to teach at least one course.
Chapter 2
Copyright © 2014 Pearson Education, Inc.
38
Figure 2-15a and 2-15b Multivalued attributes can be represented as relationships
simple
composite
Chapter 2
Copyright © 2014 Pearson Education, Inc.
39
ASSOCIATIVE ENTITIES



An entity–has attributes
A relationship–links entities together
When should a relationship with attributes instead be
an associative entity?





All relationships for the associative entity should be many
The associative entity could have meaning independent of the
other entities
The associative entity preferably has a unique identifier, and
should also have other attributes
The associative entity may participate in other relationships
other than the entities of the associated relationship
Ternary relationships should be converted to associative
entities
Chapter 2
Copyright © 2014 Pearson Education, Inc.
40
Figure 2-11a A binary relationship with an attribute
Here, the date completed attribute pertains specifically to the
employee’s completion of a course…it is an attribute of the
relationship.
Chapter 2
Copyright © 2014 Pearson Education, Inc.
41
Figure 2-11b An associative entity (CERTIFICATE)
Associative entity is like a relationship with an attribute, but it is
also considered to be an entity in its own right.
Note that the many-to-many cardinality between entities in Figure
2-11a has been replaced by two one-to-many relationships with
the associative entity.
Chapter 2
Copyright © 2014 Pearson Education, Inc.
42
Figure 2-13c An associative entity – bill of materials structure
This could just be a relationship with
attributes…it’s a judgment call.
Chapter 2
Copyright © 2014 Pearson Education, Inc.
43
Figure 2-18 Cardinality constraints in a ternary relationship
Chapter 2
Copyright © 2014 Pearson Education, Inc.
44
Figure 2-19 Simple example of time-stamping
Time stamp – a time value that is
associated with a data value, often
indicating when some event occurred that
affected the data value
Chapter 2
The Price History
attribute is both
multivalued and
composite
Copyright © 2014 Pearson Education, Inc.
45
Figure 2-21
Data model for Pine
Valley Furniture
Company in
Microsoft Visio
notation
Different modeling
software tools may have
different notation for the
same constructs
Chapter 2
Copyright © 2014 Pearson Education, Inc.
46
All rights reserved. No part of this publication may be reproduced, stored in a
retrieval system, or transmitted, in any form or by any means, electronic,
mechanical, photocopying, recording, or otherwise, without the prior written
permission of the publisher. Printed in the United States of America.
Copyright © 2014 Pearson Education, Inc.
47